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Article

Tourist Walkability in Traditional Villages: The Role of Built Environment, Shareability, and Personal Attributes

by
Tze Ming Leung
1,
Siyu Miao
2,
Minqi Lin
3,
Huiying (Cynthia) Hou
3 and
Ming Sun
1,*
1
Hunan Provincial Key Laboratory of Intelligent Protection and Utilization Technology in Stone and Brick Cultural Relics, Hunan University of Science and Engineering, Yongzhou 425199, China
2
School of Economics and Management, Hunan University of Science and Engineering, Yongzhou 425199, China
3
Department of Building Environment and Energy Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR, China
*
Author to whom correspondence should be addressed.
Sustainability 2025, 17(12), 5311; https://doi.org/10.3390/su17125311
Submission received: 27 March 2025 / Revised: 3 June 2025 / Accepted: 4 June 2025 / Published: 9 June 2025
(This article belongs to the Section Tourism, Culture, and Heritage)
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Abstract

Tourist walkability is essential for sustainable tourism in traditional villages, where walking is often the primary mode of exploration. However, few studies have examined walkability from tourists’ perspectives, especially in village settings. This study investigates how immediate built environment perceptions, shareability (defined as the capacity of a place to encourage social media sharing), and personal attributes affect tourist walkability in traditional villages. A questionnaire survey was conducted in two traditional villages in Yongzhou, Hunan, to explore these relationships. The results reveal that the perceived quantity of traditional architecture strongly influences tourist walkability, while among built environment features, artificial features exert a greater overall impact than natural ones. Moreover, shareability plays a significant role in enhancing walkability, whereas personal attributes, though influential, have a relatively smaller effect. As the majority of survey participants were aged 18–24, these findings are particularly relevant to understanding the tourism preferences of Generation Z, a cohort with growing influence in the tourism market. These insights provide valuable guidance for designers, tourism developers, and authorities aiming to enhance walkability, promote sustainable tourism, and revitalise culturally rich traditional villages.

1. Introduction

Walking plays a significant role in travel, with tourists prepared to walk distances of 10 to 35 km per day [1]. It is a fundamental activity for tourists [2], and walkable destinations tend to attract more tourists [3]. Many tourists consider walking to be the most authentic way to experience a place, as it allows deeper engagement with the surroundings [4,5]. Moreover, walking has been identified as a key element for promoting sustainable tourism in historic areas [6]. In this context, the notion of walkability, which refers to the degree to which an environment facilitates and encourages pedestrian movement [7], becomes crucial.
Walkability is influenced by a complex interaction of physical and perceptual factors [8]. Physical infrastructure in the built environment such as the presence and quality of sidewalks, street connectivity, traffic volume and speed, and the availability of pedestrian crossings play a significant role [9]. Features like shade, greenery, and the overall attractiveness of the immediate built environment can enhance the walking experience and encourage pedestrian activity [10]. Conditions of the immediate built environment, such as perceived cleanliness [11] and safety [12], in terms of both traffic and crime, significantly shape an individual’s willingness to walk. In addition, personal attributes like gender and age [13] also influence walkability.
Despite extensive research on factors affecting walkability, a significant research gap is that most studies have not focused on the unique perspective of tourists, which likely differs from those of local residents [14]. Additionally, social media sharing has become an integral part of modern tourism behaviour in recent years. Studies have confirmed that travel information on social media platforms affected tourist behaviours [15,16]. Sharing en route via social media can influence the mood [16] and travel experiences [17,18] of the travellers. Given the connection between social media sharing and tourists’ experiences en route, it is reasonable to assume that a place’s capacity to encourage social media sharing, referred to in this study as “shareability” or “social media worthiness”, may also affect walkability. However, previous studies have primarily explored how social media sharing enhances travel experiences. Little research has examined whether and how shareability influences tourist walkability.
Traditional villages, with their rich history, cultural heritage, and local knowledge, offer compelling prospects for sustainable tourism development, serving as a driving force for protection and revitalisation of these villages [19,20]. Visitors to these villages are drawn by the opportunity to experience local customs [21] and connect with traditional architecture [22], which can offer authentic cultural experiences and foster cross-cultural understanding. Unlike urban areas, walking is often the primary way for tourists to experience traditional villages, as these villages often lack infrastructure designed for vehicles. Moreover, the settings of the built environment in traditional villages differ significantly from urban areas, being shaped by cultural and historical factors rather than modern urban planning principles. However, existing research on tourist walkability, which largely focuses on cities with vehicle traffic [23], may not apply to these settings. Given that tourist walkability can enhance revisit intentions at heritage destinations [24], it is crucial to explore tourist walkability of traditional villages.
Accordingly, this study aims to investigate tourist walkability in traditional villages by addressing the following research questions:
  • How does the perception of the immediate built environment affect tourist walkability in traditional villages?
  • To what extent does a place’s shareability influence tourist walkability?
  • How do personal attributes contribute to variations in tourist walkability?
  • What is the relative importance of these factors in influencing tourist walkability?
By examining how the perception of the built environment, a place’s capacity to encourage social media sharing, and personal attributes influence tourist walkability, this study provides insights essential for sustainable tourism development in traditional villages. Understanding the relative importance of these factors is particularly critical for prioritising strategies that enhance tourist experiences, foster cultural heritage preservation, and strengthen revisit intentions.

2. Literature Review

2.1. Theoretical Foundations of Walkability

Walkability, broadly defined as the extent to which an environment facilitates walking [7], has been extensively studied in urban planning and design. It is recognised as a key factor in creating vibrant and liveable communities [25,26,27]. Scholars have explored walkability through the development of indices [28,29,30,31] and by investigating its benefits, including health [32,33], environmental [34,35], social [36,37], and economic [38,39] benefits. Tremendous efforts have also been devoted to investigating how factors such as the built environment [9,12,40], socio-demographics [41,42], and attitudes towards walking [43,44] affect walkability.
The concept of walking needs [45] is frequently employed to explain walkability [46,47,48]. These needs are organised hierarchically in five levels of needs, namely, feasibility, accessibility, safety, comfort, and pleasurability (Figure 1). Feasibility, the most basic need, refers to the practical aspects that enable walking, such as time and mobility. Accessibility refers to the availability of routes and distances to the destinations. Safety addresses the perception of personal security associated with crime. Comfort refers to the level of ease, convenience, and contentment experienced while walking. Pleasurability, at the highest level of the needs, refers to how enjoyable and interesting when one is walking. Generally, lower-level needs should be satisfied before individuals consider higher-level needs, although complete satisfaction is not necessary. Additionally, the higher-level needs (comfort and pleasurability) are mainly affected by the immediate built environment [45,49]. Notably, the concept of walking needs has also been utilised to understand tourist walkability [50,51]. In this study, focus is directed toward the higher-level needs of comfort and pleasurability. It is assumed that the lower-level needs (i.e., feasibility, accessibility, and safety) are adequately met.

2.2. Tourist Walkability

Tourist walkability is a distinct concept within the broader walkability literature. It refers to the degree to which the built environment facilitates walking for tourists by providing walkable pathways to various destinations, without undue time and effort [52]. Previous research indicates that walking is the most popular outdoor activity of tourists [53,54]. For example, a survey revealed that the primary activity of tourists in Heidelberg old town was walking [55]. Walkable destinations should help enhance visitor experience [56] and attract more tourists [3]. As suggested by Hall et al. [4], “walking around a destination to experience the place is an attraction in its own right”. Furthermore, enhancing tourist walkability not only improves tourist experience but also supports sustainable tourism by reducing reliance on vehicular transport. All these studies suggest the importance of tourist walkability in a destination.
While tourist walkability overlaps with the broader concept of walkability in aspects such as the need for safe, accessible, and comfortable walking environments [50,51], it also encompasses unique challenges and expectations specific to tourist. Unlike locals, tourists often have limited time, less familiarity with destinations, and different motivations for walking and use of spaces [14,57,58,59]. Consequently, the notion of tourist walkability deserves its own research agenda to better understand and enhance the overall experience for travellers.

2.3. Tourist Walking in Traditional Villages

Walking constitutes an essential activity for visitors to traditional villages, which are increasingly recognised as valuable assets for sustainable tourism development. Unlike urban tourism, where tourists are typically drawn to museums, theatres, shopping, and nightlife experiences [60], tourists often seek “hidden places”, authentic drinks and food, and communication with local communities when engaging in walking tourism in villages [61]. In a study on public spaces in traditional villages, it was further revealed by using an eye-tracking experiment that individuals paid the most attention to “path-orientedness” in the public spaces, which indirectly implied the importance of walking in the villages [62]. Despite the significance of walking in these environments, limited research has specifically examined tourist walkability in traditional villages. Investigating tourist walkability in traditional villages is crucial for enhancing visitors’ experiences and guiding sustainable tourism development.
Meanwhile, traditional villages often possess distinct built environment characteristics, usually featuring traditional architecture and natural landscapes [63,64]. A previous survey even suggested that key stakeholders (e.g., residents in the villages) associated with traditional villages tended to view traditional villages as “living heritage” [65]. Space configurations within these villages can be affected by natural geography [66,67], social structure [68], and culture [66,67,69]. As a result, the spatial patterns are more organic. In contrast, urban areas are often guided by formal planning principles. Streets within traditional villages are usually narrow, rendering them not suitable for vehicle traffic [70]. As a result, walking is typically the primary mode of tourist mobility in these settings. Due to these distinct built environment characteristics, the walking behaviours of tourists in traditional village should probably be different from that in urban areas with vehicle traffic. Considering the significance of walking in these villages, tourist walkability in traditional villages requires distinct theoretical consideration from urban walkability frameworks. However, it remains unclear whether established findings about tourist walkability in urban contexts are applicable to the unique spatial and cultural characteristics of traditional villages. Addressing this gap is critical not only for enhancing visitor experiences but also for informing sustainable development strategies tailored to these unique environments.

2.4. Factors Affecting Tourist Walkability

In essence, built environment [6,71], climate [72], and micro-climate [73,74], as well as personal attributes [13] can affect tourist walkability. Among these factors, this study focuses on investigating how perception of the immediate built environment and personal attributes affect tourist walkability. Therefore, the following review will mainly focus on the relationship between these factors and tourist walkability.

2.4.1. Built Environment Factors

The built environment factors affecting tourist walkability can be broadly categorised into meso and micro levels [75,76]. The meso level refers to the neighbourhood attributes such as street networks [6,77], while the micro level is primarily concerning the immediate built environment. As this study centres on how the built environment tourists can immediately perceive affects their walkability, the following review will focus on the micro level.
The immediate built environment affecting tourist walkability can be divided into artificial features such as buildings and walkways, and natural features such as greenery spaces. Among artificial features, dedicated pedestrian walkways are commonly expected by tourists when navigating streets [5]. Meanwhile, tourists’ interest in walking increased if the street views of the destination were perceived to be more attractive [71]. Destinations with distinctive architectural style would render them more walkable for tourists [78]. Tourists would also find a place walkable due to the richness of culture, the diversity in people and activities, and visual vibrancy of the destination [3]. An example of it is the blend of Portuguese and Chinese cultures and design, and the maze-like street design in Macau [51]. Coloured sidewalks, when compared to uncoloured sidewalks, were found to be able to raise tourists’ interest in walking [71]. The provision of shading devices was also found to be influencing tourist walkability [79]. Meanwhile, several studies have revealed the importance of way-finding systems. Results from a questionnaire survey for tourist walkability in Sydney and Melbourne suggested that quality way-finding systems could help improve tourist walkability [1]. It was suggested in another study that clear way-finding signposts to mark the roads to tourist attractions could enhance tourist walkability [80]. Environmental art in the destination was also found to be a factor that improved tourist walkability [81]. For natural features, the existence of public green spaces would improve tourist walkability [11,73]. A destination would also be considered more walkable if there were trees and shade [77,78,81].
On the other hand, the conditions of the immediate built environment also affect tourist walkability. Tourists would expect to feel comfortable while walking in a destination [11,79]. Well-maintained spaces would be more walkable for tourists [79]. Cleanliness was found to be an essential factor that affected tourist walkability [11,81]. The presence of speeding vehicles would influence the walking decision of tourists [82]. Walkways without obstacles could significantly enhance the tourist satisfaction of the walking system [81]. Tourists would be reluctant to walk in places that were too crowded [81]. Despite previous research on how artificial and natural features, as well as built environment conditions, affect tourist walkability, there is limited research examining their applicability in traditional villages, where unique cultural and historical contexts may alter their effects.

2.4.2. Personal Attributes

Besides environmental factors, individuals’ demographic characteristics such as gender and age [13] could influence tourist walkability. Female tourists tended to have a greater preference for refreshment facilities and hawkers than male tourists when walking on beaches [83]. The attitudes of the tourists also play a role in affecting tourist walkability. Tourist walkability was found to be enhanced if an individual had an attachment to walking [74]. Tourists’ interest in walking would be enhanced if they were informed that the norm of exploring the destination was walking [71]. They would also engage in casual walks if they had a curiosity to get a sense of the destination [51]. While previous studies have examined some personal attributes influencing tourist walkability, little is known about how prior experiences with tourism or daily walking habits interact with tourist walkability, especially in the context of traditional villages. Addressing these gaps is critical for understanding tourist behaviour in the unique settings of traditional villages.

2.4.3. Social Media Sharing

Digital culture has transformed tourism by reshaping how travellers make travel decisions [84,85], experience the destinations [86,87], and share their journeys [88,89]. With the introduction of mobile applications, tourists can conveniently access to travel information and share their travel experiences. Specifically, sharing on social media during a trip has become a habit of tourists. Previous studies suggested that contents on social media can affect tourist walkability. Tourists were willing to walk 47.1 m more if the comment rate of an attraction on social media increased by one unit, and 229.2 m more if there were additional check-ins for an attraction [13]. Meanwhile, social media sharing represents not only a post-experience activity, but also an integral component that actively shapes real-time travel experiences. When “travelling to the site”, sharing on social media and feedback received by the sharers tended to affect their mood, and might even render changes in subsequent itinerary [16]. Sharing on social media when travelling also contributed to a sense of security during the trip [90]. Sharing in real time enhanced the tourist experience by giving immediate affirmation and gratification from distant audiences, making tourists feel more engaged in their activities [91]. Using mobile social media to share travel experiences during the trip made tourists perceive their travel experiences as more informative, enjoyable, and safe [17,18]. Although previous studies have primarily explored how social media sharing enhances travel experiences, little research has examined whether and how it influences tourist walkability. The potential for social media sharing has not been explicitly incorporated as a component within walkability frameworks, especially in the context of traditional villages. To this end, this study introduces the concept of “shareability”, which refers to a location’s capacity to encourage social media sharing. This addresses a significant gap in the existing literature, where the potential for social media sharing has not been explicitly incorporated as a distinct construct within tourist walkability frameworks.
While previous studies have shown that the built environment and personal attributes can influence tourist walkability, important research gaps remain. Most notably, prior studies on tourist walkability have primarily focused on urban contexts. The specific determinants of tourist walkability in traditional villages are comparatively underexplored. Furthermore, although previous research has recognised the growing impact of digital behaviours (e.g., social media sharing) on travel experiences, few studies have explicitly examined whether and how shareability, or the capacity of a place to encourage social media sharing, affects tourist walkability.
To address these gaps, this study investigates the effects of perceived built environment, shareability, and personal attributes on tourist walkability in traditional villages. By conceptualising and empirically testing shareability as a distinct factor, this research offers new insights that advance both theory and practice in sustainable tourism and heritage management.

2.5. Conceptual Framework

Building upon Alfonzo’s hierarchy of walking needs [45], this study focuses on higher-level needs (comfort and pleasurability) and primarily explores how perceptions of immediate built environment affect tourist walkability in traditional villages. Meanwhile, previous studies suggested that apart from enjoyment [92,93,94,95], self-actualisation [96,97], self-presentation [98,99], and social interaction [100,101] are also the intentions for tourists to share their travel experiences on social media. The notion of shareability may not fit into the needs within Alfonzo’s hierarchy. Consequently, this study also empirically explores whether the notion of shareability could be conceptualised as a higher-level need which is distinct from comfort and pleasurability, particularly in the context of contemporary tourism. As a result, the hierarchy of walking needs is further extended by considering shareability as an additional dimension relevant to contemporary tourist experiences. As noted in previous research, personal attributes and experiences, which are commonly found to influence tourist walkability, are also included in this study.
Accordingly, a conceptual framework (Figure 2) was developed to explore how various factors influence tourist walkability in traditional villages. Building upon the preceding literature review, these factors are organised into three categories: perceived built environment (with sub-categories artificial features, natural features, and built environment conditions), shareability, and personal attributes. Rather than aggregating these factors into composite constructs, each factor within these categories is analysed individually to identify its specific influence on tourist walkability in traditional villages. This categorisation provides a clear structure for interpreting and discussing the relative contributions of different factors affecting tourist walkability in traditional villages.
The framework provides a comprehensive approach that emphasises empirical examination of the effects of different factors on tourist walkability. This approach enables the identification of both the most important and the less influential factors affecting tourist walkability in traditional villages, offering valuable insights for both theory and practice. Finally, the framework serves as a foundation for designing data collection and analysis methods in this study.

3. Materials and Methods

In this study, a questionnaire survey was adopted to reveal individuals’ perception of the immediate built environment and tourist walkability in traditional villages. The survey was conducted in selected villages. The questionnaire results were then analysed by XGBoost [102] version 2.10, a machine learning algorithm based on multiple decision trees.

3.1. Identification of Factors Affecting Tourist Walkability in Traditional Villages

Before the questionnaire was constructed, it was vital to identify the factors affecting tourist walkability that would be investigated in this study. An extensive literature review was performed to identify those relevant to the context of traditional villages. Besides factors previously identified to be influencing tourist walkability, factors affecting walkability for locals were also incorporated. Additionally, several factors were proposed by the authors in this study. Cleanliness of the built environment was found to be a factor affecting tourist walkability in previous studies [11,81]. Recognising water bodies as unique elements in traditional village landscapes, this study extends this concept by proposing cleanliness of water body (Water Cleanliness) as a factor which may affect tourist walkability. On the other hand, previous studies suggested that tourist walkability would be enhanced if an individual had an attachment to walking [74]. As there is likely an interrelationship between habitual walking behaviour and attachment to walking, this study proposed daily walking duration for leisure as a factor affecting tourist walkability. Meanwhile, research suggested that place attachment was positively associated with walkability [103,104]. It is likely that experiences of living in and visiting traditional villages affect attachment to such environments. Therefore, Experience of Village Living and Experience of Village Visit were proposed as factors influencing tourist walkability in traditional villages in this study. In addition, the factor “Social Media Worthiness” was proposed to represent the notion of shareability. Table 1 lists the factors examined in this study.

3.2. Site and Survey Location Selection

Several criteria were considered when selecting the sites. First, the sites had to be traditional villages. Second, villages needed to be inhabited to ensure authenticity and relevance for tourists. Third, villages had to possess diverse built environment characteristics, enabling comprehensive exploration of the factors listed in Table 1. Consequently, two traditional villages, namely Shanggantang Village and Guolan Yao Village in Yongzhou, Hunan, were selected. Figure 3 shows the locations of these two villages.
Shanggantang Village is a traditional Han village with approximately 1200 years of history. It features over 200 well-preserved residential buildings from the Ming and Qing dynasties. These buildings showcase characteristics of southern Han architectural elements, including fish scale tiles, ornamental perforated windows, and decorative wood and brick carvings. Covering an area of approximately 0.035 km2, the village has been designated as a key historical and cultural site under national-level protection. In contrast, Guolan Yao Village represents a traditional ethnic minority settlement established around 1400. It features distinctive Yao architectural styles, notably functional two-storey structures. In these structures, one level accommodates residents while the other houses livestock. With a considerably larger area of about 6 km2, this village has been recognised as part of China’s famous historical and cultural villages since 2014.
The selection of villages with distinct contexts (one Han and one Yao, one compact and one extensive) enabled the study to examine tourist walkability across a diverse range of built environment features relevant to the research questions. Although only two villages were included, this purposeful sampling enables an in-depth and context-sensitive analysis, which is foundational for exploratory research and theory development in underexplored areas [117]. Within these villages, survey locations were carefully chosen to encompass variations in traditional architecture, walking path conditions, shading provision, natural features, etc. This strategic approach enabled robust modelling and enhanced the reliability and interpretability of results. For example, one spot featured a narrow walking path (Figure 4a), while another was dominated by traditional architecture (Figure 4b). Due to the difference in area, 6 and 17 survey locations were selected in Shanggantang Village and Guolan Yao Village, respectively, resulting in a total of 23 survey locations.

3.3. Questionnaire Survey

The questionnaire survey was conducted at the selected survey locations to capture participants’ perceptions of the immediate built environment, social media worthiness, and tourist walkability. The questionnaire comprised two parts.
The first part, completed at each of the 23 survey locations, evaluated perceptions of built environment characteristics, social media worthiness, and tourist walkability using an 11-point Likert scale, except for one item asking whether participants perceived any unwanted odour, which was measured using a binary (Yes/No) response format. The underlying reason for choosing an 11-point scale for these questions was that this scale could transmit more information and increased generalisability when compared to 7- or 5-point scales [118]. Illustrative examples of these questions are shown in Figure 5a,b.
The second part, completed once by each participant, collected demographic information and personal attributes, including employment status, daily walking duration for leisure, previous experiences of living in or visiting traditional villages, and preferences for walking during travel. These attributes were measured using structured categorical and binary response formats designed specifically for this study.

3.4. Data Analysis

Data collected from the questionnaire survey was analysed by using the machine learning algorithm XGBoost. It is an algorithm which can be used to deal with both regression and classification problems. It can work effectively even for small datasets [119]. For example, the prediction model developed using XGBoost was the most accurate when examining abdominal aortic aneurysm (AAA) growth rates with 50 samples [120]. In the realm of tourism, it has been used to predict the revisit intention of tourists [121], online tourism customer purchases [122], and so on. A previous study even suggested that the possible non-linear relationship between walkability and factors affecting it could be revealed by utilising XGBoost algorithm [123]. In this study, a prediction model connecting tourist walkability (i.e., dependent variable) and the perceived immediate built environment, shareability, and personal attributes (i.e., independent variables) would be formulated. Although a prediction model for tourist walkability could be formulated by using XGBoost, this model does not reveal how the independent variables influence the dependent variable. As a result, SHAP (SHapley Additive exPlanations) algorithm [124], an explainable artificial intelligence technique, was adopted. SHAP can be used to interpret a machine learning model by evaluating the relative importance of each independent variable in predicting the outcomes (i.e., tourist walkability). It follows a game-theoretic approach to make sense of the model output. Several walkability studies have used both XGBoost and SHAP to better explain how various factors affected walkability [125] or pedestrian satisfaction [126].

4. Results

The questionnaire survey was conducted on 26 November 2023 and 9 December 2023 in the two villages. Participants were recruited from Hunan University of Science and Engineering using posters displayed around the university. A total of 105 participants were invited to visit the villages and participate in the survey. Upon arrival at the villages, the participants were encouraged to explore the villages freely before the questionnaire survey so that they could gain authentic tourist experiences. Before the survey commenced, the participants were informed that their participation was on a voluntary basis, and they could withdraw at any time. They were asked to answer the questions in the questionnaire survey as tourists to these villages.
To ensure systematic data collection and reduce potential survey order bias, participants were divided into four groups. Each group was accompanied by research team members who guided participants sequentially through the survey locations. The visiting order of these locations was deliberately varied across the groups to control for sequencing effects. Additionally, the research team closely supervised questionnaire completion at each location to ensure data accuracy and consistency. It took about 5 min to answer all questions related to tourist walkability (i.e., section 1 of the questionnaire) at each surveying spot. After completing the questionnaire, each participant was received a souvenir (costing approximately USD 10) as a reward. In total, 101 questionnaires were successfully administered. Table 2 shows the descriptive statistics of the participants.

4.1. Tourist Walkability Prediction Model Development

To obtain more meaningful results, some of the independent variables were recoded before formulating the prediction model. Specifically, all the independent variables that were nominal in nature (e.g., employment status) were recoded using one-hot encoding. As water cleanliness was only relevant when a water body was present, the variable was recoded as 1 when both the perceived quantity of water bodies and the perceived degree of water cleanliness were 7 or higher, and 0 otherwise. Furthermore, the daily walking duration for leisure was recoded as 1 if it was greater than 30 min, which aligned with the recommended guideline for personal health [127,128], and 0 otherwise.
Although the issue of multicollinearity might not affect the predictive power of the model developed by the XGBoost algorithm, it might affect the revealed importance weightings of the independent variables [129]. As a result, the variance inflation factors (VIFs) of the independent variables were calculated to examine if serious multicollinearity among the independent variables existed. The VIFs of all the identified independent variables were below 2.8, meaning that there was no serious multicollinearity issue among them. Consequently, all identified independent variables were adopted to develop the prediction model using XGBoost.
To ensure the robustness of the prediction model, this study adopted a nested validation approach for model training and evaluation. The data was first randomly divided into training (80%) and validation (20%) sets. The training set was then further randomly sub-divided to ensure robust validation, creating a secondary training subset (80%) and a validation subset (20%). These subsets were specifically used for hyperparameter tuning via Optuna [130] version 4.0.0. This nested validation procedure helps prevent the validation set from influencing hyperparameter tuning. As a result, it reduces the risk of overfitting and enhancing the predictive reliability of the model. Meanwhile, the number of trials to search for the optimised values of hyperparameters was set to 1000. It can be seen from Figure 6 that the root mean squared error (RMSE) of the model decreased sharply when the optimisation process started. The RMSE tended to be stable after 300 trials. To this end, 1000 trials were considered more than sufficient for the task of hyperparameter optimisation in this study. Eventually, a model was optimised with a correlation coefficient of 0.719 for the predicted tourist walkability and the ground truth of the validation dataset, signifying that a reasonably fit model was developed.

4.2. Importance Weightings of Factors Affecting Tourist Walkability

The Python package SHAP [131] version 0.45.1 was used to calculate the SHAP values and reveal the impact of the independent variables on the dependent variable. Figure 7 shows the SHAP summary plot, illustrating the SHAP values derived from the XGBoost model. The SHAP summary plot helps to understand the effect of each independent variable on the dependent variable for each data point. On the other hand, Figure 8 shows the absolute mean SHAP values of the independent variables, which reflect the importance weightings of the variables in affecting the dependent variable. An independent variable with a higher absolute mean SHAP value indicates a higher importance weighting. In this study, independent variables with mean absolute SHAP values lower than 0.01 were not examined as their contributions to the change in the dependent variable were considered insignificant. The top ten factors that exerted the most effects on tourist walkability were social media worthiness, cleanliness, the quantity of traditional architecture, the quantity of shading provision, the quantity of greenery, walking path width, human scale, walking path condition, building condition, and the quantity of sky.
Additionally, these absolute mean SHAP values can be aggregated to understand the collective importance of different categories of factors, as organised in the conceptual framework. It can be seen from Table 3 that the perceived built environment influenced tourist walkability the most, followed by shareability and personal attributes. It is even possible to compare the importance weightings of built and natural features within the perceived built environment categories. It was found that artificial features had a greater effect on tourist walkability when compared to natural features. Additionally, the importance weighting of built environment conditions was higher than that of natural features but slightly lower than that of artificial features. When comparing shareability, which comprised only a single factor, social media worthiness, with the perceived built environment, the importance weighting of the latter exceeded the former by 1.061−0.809 = 0.252. The importance weighting of personal attributes was found to be the lowest among all the three categories of factors affecting tourist walkability.

4.3. Effects of Individual Factors Affecting Tourist Walkability

Meanwhile, the effects of individual factors on tourist walkability were revealed. Figure 9 shows the dependence plots of these factors, which helped to examine the relationship between the individual factors and tourist walkability.

4.3.1. Perceived Immediate Built Environment

Concerning the artificial features of the immediate built environment, the effect of traditional architecture on tourist walkability was similar when the perceived quantity of traditional architecture was below 4. Beyond the value of 4, the perceived quantity of traditional architecture exhibited a positive relationship with tourist walkability. On the other hand, it was found that the effect of shading provision on tourist walkability was positive when the perceived quantity of shading provision was below the value of 6. However, the effect of shading provision on tourist walkability did not differ significantly beyond this point. For the walking path, tourist walkability was basically enhanced if individuals perceived it to be wider. Additionally, tourist walkability did not change significantly when the perceived degree of human scale was below the value of 3. Tourist walkability increased with the perception of human scale beyond this point, and its effect became stable again when the perceived degree of human scale was higher than 7. Meanwhile, tourist walkability was found to be lower when a place was perceived to be more enclosed.
As per the natural features, there was generally a positive relationship between the perceived quantity of greenery and tourist walkability. In contrast, a fluctuating trend was observed for the effect of water body on tourist walkability. Tourist walkability increased when the perceived quantity of water bodies was below the value of 4. The trend reversed when the perceived quantity of water bodies was between the values of 4 and 7. Beyond the value of 7, tourist walkability increased with the perceived quantity of water bodies again. For the sky, tourist walkability decreased if the perceived quantity of sky was below the value of 5. However, an increasing trend was observed when the value was above 5.
The various factors under the umbrella of built environment conditions also affected tourist walkability differently. Tourist walkability would be enhanced if individuals perceived the environment to be cleaner. Similarly, if water body existed and the water was perceived to be clean, tourist walkability would be higher. For the effect of walking path condition, tourist walkability increased with the perceived degree of walking path condition if it was below the value of 6. The effect of walking path condition did not change significantly beyond this point. The effect of building condition remained relatively constant when its perceived degree was below 4. Tourist walkability would increase beyond this point until the perceived degree of building condition attained the value of 7. Afterwards, the effect of building condition on tourist walkability basically did not change. The relationship between obstacles and tourist walkability was relatively unstable but a general decreasing trend was exhibited.

4.3.2. Shareability

Shareability was represented by the social media worthiness. When the perceived degree of social media worthiness was between 0 and 2, its effect on tourist walkability did not change significantly. However, the trend was different afterwards. There was a clear positive linear relationship between social media worthiness and tourist walkability when the perceived degree of social media worthiness was above the value of 2.

4.3.3. Personal Attributes

Demographic characteristics of individuals played a role in affecting tourist walkability. Female respondents tended to report higher levels of tourist walkability. Additionally, individuals’ habits and experiences also contributed to differences in tourist walkability. When an individual had the habit of walking for more than 30 min per day, or had resided in traditional villages until tertiary education, tourist walkability was enhanced. Conversely, tourist walkability was found to be lower if an individual had visited other traditional villages for tourism before.

5. Discussion

This study revealed the key factors influencing tourist walkability in traditional villages by developing an XGBoost-based prediction model that links tourist walkability to the perceived immediate built environment, shareability, and personal attributes. The findings are particularly relevant to Generation Z (born between 1997 and 2012) given that younger respondents comprised the majority of the samples in the questionnaire survey. According to a report by McKinsey [132], Generation Z travellers lead all generations in travel enthusiasm, taking nearly five trips annually, dedicating 29% of their income to travel, and showing the strongest increased interest (76%) in post-pandemic travel. This implies the importance of Generation Z in the tourism sector.
Specifically, the results of this study indicated that the immediate built environment and shareability played dominant roles in shaping tourist walkability, while certain personal demographics, habits, and experiences exerted subtle yet noteworthy influences. These findings underscore the multidimensional nature of tourist walkability and highlight the importance of integrating environmental enhancements with targeted visitor engagement strategies in future tourism development policies for walking tourism in traditional villages.

5.1. Walking Needs Underpinning Tourist Walkability

In this study, it was found that shareability—represented by social media worthiness—was crucial to tourist walkability. Tourist walkability generally increased with higher perceptions of social media worthiness. Similarly to the higher-order needs of comfort and pleasurability in Alfonzo’s hierarchy of walking needs [45], previous studies have indicated that features of the immediate built environment strongly influence social media engagement. Natural, traffic-related, and artificial features in the built environment could affect the rating of restaurants located within it on social media websites [133]. The density of catering establishments tended to encourage social media check-ins and reviews [134], while aesthetic design significantly impacted tourists’ intentions to post on social media [135]. Additionally, the integration of natural elements and architectural design has been identified as a popular theme for social media sharing in built environments [136].
Building upon the empirical results from this study, as well as the findings from previous research, this study proposes an extension of Alfonzo’s hierarchy of walking needs specifically adapted for tourist walkability (illustrated in Figure 10). This extension explicitly introduces ‘shareability’, or social media worthiness, as a novel dimension to capture contemporary social media-driven tourist behaviours. Considering that besides perceived enjoyment [92,93,94,95], self-actualisation [96,97], self-presentation [98,99], and social interaction [100,101] are also the primary motivations behind social media sharing, shareability could be positioned alongside pleasurability as a parallel higher-level need in Alfonzo’s hierarchy.
The findings regarding the relationship between shareability and walkability contribute to theory by empirically demonstrating that shareability, which relates to tourists’ motivation to share travel experiences on social media, significantly shapes tourist walkability in traditional villages. By extending Alfonzo’s hierarchy of walking needs to incorporate shareability as a potential higher-level motivation, this research responds to the evolving dynamics of contemporary tourism, where digital engagement increasingly influences both destination choice and movement patterns. This suggests that the conventional framework for studying tourist walkability, which primarily focuses on physical or experiential needs, may require adaptation to remain relevant in digitally mediated tourism contexts.

5.2. Immediate Built Environment and Tourist Walkability in Traditional Villages

By using SHAP values, the importance weightings of the factors affecting tourist walkability in traditional villages have been revealed. Traditional architecture, which can be used to develop cultural-based tourism products [137], was found to be the most important built environment feature affecting tourist walkability. In addition, it was also found in this study that tourist walkability would be enhanced if the perceived quantity of traditional architecture was higher than the value of 4, while the effect of the existence of traditional architecture on tourist walkability was nearly constant when the perceived quantity was below 4. This observation is generally consistent with a previous study that found tourists strongly preferred traditional architecture over modern constructions [138]. This preference likely stems from traditional architecture’s dual role as both a physical heritage and a cultural anchor that embodies local heritage, construction techniques, and community history. Furthermore, traditional villages are often perceived as “living heritage” [65], where historical authenticity and daily life coexist. In this context, traditional architecture serves as the physical manifestation of this heritage. This integration of heritage significance and functional environment may explain why tourists perceive areas with more traditional architecture as more walkable—they offer both physical pathways and meaningful cultural experiences simultaneously. It has been suggested that traditional architecture should be appealing to tourists and encourage them to take photos [139], reflecting how these structures simultaneously enhance tourist walkability while fulfilling tourists’ desire for authentic cultural experiences. It has also been suggested in a previous study that the tourists in traditional villages evaluated the conservation of heritage, which was mainly the artificial features such as traditional architecture in the built environment, as an important factor in affecting their visit satisfaction [140]. Meanwhile, a distinct architectural style and richness of culture should enhance tourist walkability [3,51,78]. This study has taken one step further to understand the importance weighting of traditional architecture in influencing tourist walkability compared to other factors. From a practical point of view, the results concerning traditional architecture and walkability in this study can complement previous studies suggesting that tourists were satisfied by the architectural and atmospheric features of hotels in historic buildings [141]. The existence of traditional buildings can both enhance tourist walkability of the outdoor space and the experience provided by the building interiors.
Additionally, this study investigated the aggregated importance weightings of various factors affecting tourist walkability. In terms of built environment features, previous studies confirmed that both the artificial features [3,51,78,79] and natural features [11,73] were important factors affecting tourist walkability. There have also been studies on walkability for locals which revealed the importance weightings of some immediate built environment features [142,143]. For instance, one study examined walkability perception using panoramic street view images and revealed the relative importance of features such as vegetation, sidewalks, and sky [144]. Another study investigated importance weightings of built environment features such as trees, sidewalks, and ramps when proposing a comfort walkability index [107]. However, few studies explicitly examined the aggregated importance weightings of artificial and natural features. In this study, it was found that artificial features exerted more influence on tourist walkability in traditional villages than natural features. This observation aligns with a study on attractions in traditional village tourism which found that the combined weighting of artificial features, such as streets and squares, residence, and public buildings, were higher than that of water and vegetation [145]. While it is important to introduce natural features such as greenery in traditional villages, more attention should be given to the artificial built environment features (such as shading provision, the second most important built environment feature) when developing village tourism, in order to enhance tourist walkability in the villages. Furthermore, the built environment conditions were also found to be vital in affecting tourist walkability, implying that the maintenance of the built environment is crucial to make the traditional villages walkable for tourists.

5.3. Policy and Practical Implications

The findings of this study offer actionable insights for policymakers and tourism developers aiming to enhance tourist walkability and promote sustainable tourism in traditional villages.
First, the results indicate that artificial features have a greater aggregated importance than natural features in influencing tourist walkability. This underscores the need for policies that prioritise the preservation and enhancement of artificial features in the built environment, particularly traditional architecture, which was identified as the most significant among built environment features. Specifically, policies should focus on maintaining and restoring traditional architectural structures to preserve cultural identity while improving walkability. This could include financial incentives for homeowners to maintain traditional facades, guidelines for appropriate restoration techniques, and restrictions on incompatible modern additions in the historic cores of villages.
Second, cleanliness was found to be the most critical factor across all built environment conditions. This highlights the importance of implementing policies that ensure cleanliness of public spaces, walking paths, and surrounding environments in traditional villages. Resources could be allocated to employ local residents to maintain the cleanliness of outdoor spaces in traditional villages. This approach not only enhances tourist walkability but also helps retain village population by providing job opportunities to residents. This enables more sustainable development of the villages.
Third, the study emphasises the role of shareability, or social media worthiness, in enhancing tourist walkability. Policymakers may consider integrating visually distinctive design elements that promote photo opportunities along walking routes to encourage social media engagement. Temporary installations or festivals that could encourage digital sharing could also be considered. Additionally, expanding digital infrastructure within traditional villages (such as Wi-Fi access or interactive way-finding aids) may further support tourists’ ability to share their travel experiences on social media en route. On one hand, this can help enhance tourist walkability. On the other hand, user-generated content shared on social media platform can help promote village tourism.
By addressing these factors, policymakers can create more walkable environments that enhance tourist satisfaction while contributing to traditional village revitalization.

5.4. Limitations and Future Studies

This study is not without limitations. First, this study employed rigorous internal validation by systematically dividing the data into training and validation sets, ensuring the reliability of the current findings. Nevertheless, external validation was beyond the scope of this study. Future research would benefit from conducting external validation through separate or longitudinal datasets to further confirm the robustness and generalisability of these findings. Second, most respondents were aged between 18 and 24 years (81.2%) and were predominantly students (91.1%) recruited from a university in this study. As discussed, the findings from this study are more relevant to Generation Z due to the demographic of the participants. While this demographic represents an important segment of the tourism market, caution should be exercised in generalising findings beyond younger tourists. Different age groups may have different preferences, priorities, and behaviours regarding tourist walkability in traditional villages. Future studies should include authentic tourists from different age groups as respondents. This will help better understand the walking preferences of tourists in general. Third, limitations exist as the data collection was conducted in two villages on two specific days (26 November and 9 December 2023) during winter. While focusing on two villages with distinct cultural and spatial characteristics allowed for in-depth, context-sensitive analysis, it does not capture the regional diversity of traditional villages in China. The relatively narrow timeframe may not be able to account for seasonal variations that could impact tourist walkability perceptions. Factors such as weather conditions and seasonal foliage changes may potentially affect tourist walkability. Consequently, the findings may not be fully generalisable to other times of year or to all traditional village settings. Nonetheless, this exploratory approach provides valuable initial insights and highlights key factors for future research. Further studies should include a larger and more varied sample of villages and consider data collection across multiple seasons. Fourth, the measurement of shareability through a single item (Social Media Worthiness) may not fully capture the complexity of this construct. A single-item measure can have limitations in terms of reliability and validity compared to multi-item scales. However, previous studies suggested that single-item measures could be a viable option when the research situation is exploratory [117,146]. The use of a single-item measure in this study is considered reasonable due to the exploratory nature of this study concerning the novel concept of shareability in tourist walkability. Future studies could develop and validate a more comprehensive multi-item scale for measuring shareability in tourism contexts, which would enhance the robustness of findings related to this important construct. It will also be of interest to examine how the built environment features affect shareability in future studies. Fifth, this study revealed the relationship between tourist walkability and the perceived immediate built environment. It will be of interest to quantify the built environment features using objective measures in future studies. Examining both subjective perceptions and objective characteristics of the walking environment will provide a more complete understanding of tourist walkability. Despite these limitations, this study can provide insights for designers and authorities who aim to develop sustainable tourism by enhancing tourist walkability in traditional villages.

6. Conclusions

To the best of the authors’ knowledge, this study is the first to empirically introduce and examine the concept of shareability, defined as the capacity of a place to encourage social media sharing, as a distinct dimension within the framework of tourist walkability. Unlike prior research which primarily focused on urban context, this study explores tourist walkability in traditional villages with unique spatial and cultural configurations. By adopting a questionnaire survey in two traditional villages in Hunan, China, this study provides new evidence on how the perceived immediate built environment, shareability, and personal attributes affect tourist walkability in these unique settings. This study not only identifies the relative importance of various factors in affecting tourist walkability but also extends existing theory by incorporating digital-age behaviours into tourist walkability frameworks, reflecting the evolving realities of contemporary tourism.
Notably, shareability emerged as an essential component contributing to tourist walkability, indicating that environments designed to encourage social media engagement can significantly enhance tourists’ walking experiences. Among built environment features, the perceived amount of traditional architecture was the most important factor affecting tourist walkability. Additionally, artificial features influenced tourist walkability more than natural features.
By highlighting the importance of shareability as a higher-level walking need alongside pleasurability, the findings of this study extend the established theoretical framework of the hierarchy of walking needs to better reflect the impact of digital culture, especially social media sharing, on tourism. Positioning shareability as a core component of tourist walkability, this study provides a conceptual foundation for future research on how digital culture shapes mobility in a variety of tourism settings.
While the findings are particularly relevant to Generation Z tourists who formed the majority of the sample, they provide valuable insights for enhancing tourist walkability in traditional villages. The identified importance of traditional architecture and artificial features provides clear direction for policymakers to prioritise conservation efforts, while the significance of shareability highlights the need to create socially engaging environments. As walking is an important means of travelling in traditional villages, results from this study can inform designers and authorities on how to enhance the walking environment when attempting to revitalise these villages through tourism development.

Author Contributions

Conceptualization, T.M.L. and M.S.; methodology, T.M.L. and M.L.; formal analysis, T.M.L. and M.L.; writing—original draft preparation, T.M.L.; writing—review and editing, S.M. and H.H.; supervision, T.M.L., S.M. and M.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by Hunan Provincial Social Sciences Achievements Evaluation Committee, project numbers XSP2023LSC002 and XSP25YBC597, and Special Fund for Science Popularization of Hunan Innovative Province Construction, project number 2024ZK4022.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Ethics Committee of Hunan University of Science and Engineering (protocol code 2025-TH-001 and date of approval 6 November 2023).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Hierarchy of walking needs [45].
Figure 1. Hierarchy of walking needs [45].
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Figure 2. Conceptual framework of this study.
Figure 2. Conceptual framework of this study.
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Figure 3. Locations of Shanggantang Village and Guolan Yao Village.
Figure 3. Locations of Shanggantang Village and Guolan Yao Village.
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Figure 4. Examples of surveying locations with (a) narrow walking path and (b) predominantly traditional architecture.
Figure 4. Examples of surveying locations with (a) narrow walking path and (b) predominantly traditional architecture.
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Figure 5. Examples of questions for eliciting (a) social media worthiness, (b) tourist walkability.
Figure 5. Examples of questions for eliciting (a) social media worthiness, (b) tourist walkability.
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Figure 6. RMSE of trial searches to optimise hyperparameters of the XGBoost model.
Figure 6. RMSE of trial searches to optimise hyperparameters of the XGBoost model.
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Figure 7. SHAP values of the independent variables.
Figure 7. SHAP values of the independent variables.
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Figure 8. Absolute mean SHAP values of the independent variables.
Figure 8. Absolute mean SHAP values of the independent variables.
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Figure 9. Dependence plots of the independent variables.
Figure 9. Dependence plots of the independent variables.
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Figure 10. Proposed theory of walking needs for tourist walkability.
Figure 10. Proposed theory of walking needs for tourist walkability.
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Table 1. Factors affecting tourist walkability examined in this study.
Table 1. Factors affecting tourist walkability examined in this study.
Category FactorDescriptionReference
Perceived Immediate Built
Environment		Artificial FeaturesWalking Path WidthPerceived width of walking path* [105,106,107]
Traditional ArchitecturePerceived amount of traditional architecture[3,51,78]
Shading ProvisionPerceived amount of shading provision[79]
Human ScalePerceived degree of human scale* [108]
EnclosurePerceived degree of enclosure* [108,109]
Natural FeaturesGreeneryPerceived amount of greenery[11,73]
Water BodyPerceived amount of water bodies* [10]
SkyPerceived amount of sky* [110]
Built Environment
Conditions		OdourPerceived odour* [111]
CleanlinessPerceived degree of cleanliness[11,81]
ObstaclePerceived amount of obstacles along walking path[79,81]
Water CleanlinessPerceived degree of water cleanliness (when water body exists)Proposed in this study
Walking Path ConditionPerceived condition (well-maintained or not) of walking path* [112,113]
Building ConditionPerceived condition (well-maintained or not) of buildings* [114,115]
Shareability Social Media WorthinessPerceived degree of worthiness to take pictures and share on social mediaProposed in this study
Personal AttributesDemographicAgeAge of participants[13]
CharacteristicsGenderGender of participants[13,83]
Employment StatusEmployment status of participants* [116]
Habits and ExperiencesDaily Walking Duration for LeisureParticipants’ daily strolling durationProposed in this study
Walking Preference when TravellingParticipants’ preference for walking while travelling[74]
Experience of Village LivingParticipants’ experience of living in traditional villagesProposed in this study
Experience of Village VisitParticipants’ experience of visiting traditional villagesProposed in this study
* Factors borrowed from studies on walkability for locals.
Table 2. Descriptive statistics of the participants in the questionnaire survey.
Table 2. Descriptive statistics of the participants in the questionnaire survey.
Variable Counts
GenderM58 (57.4%)
F43 (42.6%)
AgeBelow 1810 (9.9%)
18–2482 (81.2%)
25–343 (3.0%)
35–443 (3.0%)
45–541 (1.0%)
55–642 (2.0%)
Employment StatusStudent92 (91.1%)
Employed7 (6.9%)
Unemployed0 (0%)
Retired2 (2.0%)
Monthly Expenses (RMB)1000 or below6 (5.9%)
1001–150061 (60.4%)
1501–200027 (26.7%)
2001–25007 (6.9%)
Daily Walking Duration for Leisure (mins)07 (6.9%)
1–1518 (17.8%)
16–3037 (36.6%)
31–4520 (19.8%)
46–607 (6.9%)
Above 6012 (11.9%)
Residence in Traditional VillagesNever15 (14.9%)
Until Primary Education25 (24.8%)
Until Secondary Education22 (21.8%)
Until Tertiary Education21 (20.8%)
Only During Vacations18 (17.8%)
Visited other Villages BeforeYes66 (65.3%)
No35 (34.7%)
Prefer Walking when TravellingYes82 (81.2%)
No19 (18.8%)
Table 3. Aggregated importance weightings of different categories affecting tourist walkability.
Table 3. Aggregated importance weightings of different categories affecting tourist walkability.
CategoryAggregated Importance Weighting
Perceived built environment1.061Artificial Features0.429
Natural Features0.214
Built Environment Conditions0.418
Shareability0.809
Personal attributes0.105
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Leung, T.M.; Miao, S.; Lin, M.; Hou, H.; Sun, M. Tourist Walkability in Traditional Villages: The Role of Built Environment, Shareability, and Personal Attributes. Sustainability 2025, 17, 5311. https://doi.org/10.3390/su17125311

AMA Style

Leung TM, Miao S, Lin M, Hou H, Sun M. Tourist Walkability in Traditional Villages: The Role of Built Environment, Shareability, and Personal Attributes. Sustainability. 2025; 17(12):5311. https://doi.org/10.3390/su17125311

Chicago/Turabian Style

Leung, Tze Ming, Siyu Miao, Minqi Lin, Huiying (Cynthia) Hou, and Ming Sun. 2025. "Tourist Walkability in Traditional Villages: The Role of Built Environment, Shareability, and Personal Attributes" Sustainability 17, no. 12: 5311. https://doi.org/10.3390/su17125311

APA Style

Leung, T. M., Miao, S., Lin, M., Hou, H., & Sun, M. (2025). Tourist Walkability in Traditional Villages: The Role of Built Environment, Shareability, and Personal Attributes. Sustainability, 17(12), 5311. https://doi.org/10.3390/su17125311

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